SAR village targets extraction and heterogonous image registration. Issue 21 (16th October 2019)

• Record Type: Journal Article
• Authors: Li, Qixue; Yin, Kuiying
• Is Part Of: Journal of engineering. Volume 2019:Issue 21(2019)
• Page Start: 8056
• Page End: 8060
• Publication Date: 2019-10-16
• Subjects: synthetic aperture radar -- median filters -- optical images -- image matching -- image texture -- feature extraction -- radar imaging -- image registration -- speckle -- partial differential equations -- image denoising -- matrix algebra -- Fourier analysis -- image filtering; heterogonous image registration -- SAR village targets extraction -- signal‐to‐noise ratio -- synthetic aperture radar image -- optical images -- partial differential method -- SAR image matching -- synthetic aperture radar -- median filter -- speckle noise removal -- grey level cooccurrence matrix algorithm -- texture parameters -- regions of interest -- ROI -- false alarm areas -- local‐grey‐level congruency method -- Fourier descriptors -- morphological algorithms -- boundary features -- HU moment invariants -- Euclidean distance -- cosine similarity measurements -- root‐mean‐square‐error; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2019.0702
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : Since the signal‐to‐noise ratio of synthetic aperture radar (SAR) image is low, it is difficult to match SAR images with optical images accurately. A new method of SAR village targets extraction and heterogonous image registration is proposed in this study. Median filter and partial differential method are first used to remove speckle noise; next, the grey level co‐occurrence matrix algorithm is used by calculating four typical texture parameters of it to obtain preliminary regions of interest (ROI) of village targets and false alarm areas are cleared by proposed local‐grey‐level congruency method; then proper numbers of Fourier descriptors and morphological algorithms are used to describe ROI again to maintain the boundary features of targets better. Finally, HU moment invariants, which is combined with Euclidean distance and cosine similarity measurements, are utilised to achieve heterogonous image registration. The experimental results show that the root‐mean‐square‐error of the registration image is small and the heterogonous registration image is accurate, demonstrating that the authors' method is stable and accurate, and owns certain research value and broad application prospect as well.